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Forest Orchids under Future Climate Scenarios: Habitat Suitability Modelling to Inform Conservation Strategies.
Pica, Antonio; Vela, Daniele; Magrini, Sara.
Afiliação
  • Pica A; Department of Ecological and Biological Sciences, University of Tuscia, 01100 Viterbo, Italy.
  • Vela D; Department of Ecological and Biological Sciences, University of Tuscia, 01100 Viterbo, Italy.
  • Magrini S; Department of Ecological and Biological Sciences, University of Tuscia, 01100 Viterbo, Italy.
Plants (Basel) ; 13(13)2024 Jun 30.
Article em En | MEDLINE | ID: mdl-38999650
ABSTRACT
Orchidaceae is one of the largest and most diverse families of flowering plants in the world but also one of the most threatened. Climate change is a global driver of plant distribution and may be the cause of their disappearance in some regions. Forest orchids are associated with specific biotic and abiotic environmental factors, that influence their local presence/absence. Changes in these conditions can lead to significant differences in species distribution. We studied three forest orchids belonging to different genera (Cephalanthera, Epipactis and Limodorum) for their potential current and future distribution in a protected area (PA) of the Northern Apennines. A Habitat Suitability Model was constructed for each species based on presence-only data and the Maximum Entropy algorithm (MaxEnt) was used for the modelling. Climatic, edaphic, topographic, anthropogenic and land cover variables were used as environmental predictors and processed in the model. The aim is to identify the environmental factors that most influence the current species distribution and the areas that are likely to contain habitats suitable for providing refuge for forest orchids and ensuring their survival under future scenarios. This will allow PA authorities to decide whether to invest more resources in conserving areas that are potential refuges for threatened species.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article